Triple

T13523573
Position Surface form Disambiguated ID Type / Status
Subject South Bolaang Mongondow Regency E322962 entity
Predicate capital P234 FINISHED
Object Molibagu
Molibagu is a town in North Sulawesi, Indonesia, serving as the administrative and economic center of South Bolaang Mongondow Regency.
 E1045179 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Molibagu | Statement: [South Bolaang Mongondow Regency, capital, Molibagu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Molibagu
Context triple: [South Bolaang Mongondow Regency, capital, Molibagu]
  • A. Mabor
    Mabor is a tire brand owned by Continental AG, known for producing affordable passenger and commercial vehicle tires.
  • B. Muyil
    Muyil is an ancient Maya archaeological site in Mexico’s Yucatán Peninsula, known for its well-preserved temples and proximity to the Sian Ka'an Biosphere Reserve.
  • C. Mosogar
    Mosogar is a prominent Urhobo community in Delta State, Nigeria, known as one of the major clans of the Urhobo ethnic group.
  • D. Matabaan
    Matabaan is a town in central Somalia that serves as one of the urban centers within the federal member state of Hirshabelle.
  • E. Molazzana
    Molazzana is a small municipality in Tuscany, central Italy, known for its scenic location in the Garfagnana area of the Apennine mountains.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Molibagu
Triple: [South Bolaang Mongondow Regency, capital, Molibagu]
Generated description
Molibagu is a town in North Sulawesi, Indonesia, serving as the administrative and economic center of South Bolaang Mongondow Regency.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Molibagu
Target entity description: Molibagu is a town in North Sulawesi, Indonesia, serving as the administrative and economic center of South Bolaang Mongondow Regency.
  • A. Mabor
    Mabor is a tire brand owned by Continental AG, known for producing affordable passenger and commercial vehicle tires.
  • B. Muyil
    Muyil is an ancient Maya archaeological site in Mexico’s Yucatán Peninsula, known for its well-preserved temples and proximity to the Sian Ka'an Biosphere Reserve.
  • C. Mosogar
    Mosogar is a prominent Urhobo community in Delta State, Nigeria, known as one of the major clans of the Urhobo ethnic group.
  • D. Matabaan
    Matabaan is a town in central Somalia that serves as one of the urban centers within the federal member state of Hirshabelle.
  • E. Molazzana
    Molazzana is a small municipality in Tuscany, central Italy, known for its scenic location in the Garfagnana area of the Apennine mountains.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa535cc81908d0018fef81a2848 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7549c016c8190945a185b2bc20689 completed May 3, 2026, 1:58 p.m.
NEDg Description generation batch_69f75574d25881908c6fdef3f35cba85 completed May 3, 2026, 2:02 p.m.
NED2 Entity disambiguation (via description) batch_69f7561f170c8190b12c79fbbe57ad91 completed May 3, 2026, 2:05 p.m.
Created at: April 9, 2026, 9:44 p.m.